The author argues that AI agents will soon handle nearly the entire software development lifecycle—writing code, reviewing it, testing, debugging, and deployment—leaving humans to focus on what machines can't do well. He's making two big bets: first, that agents will eventually master the parts they're currently mediocre at (code review, maintenance, shipping to production), and second, that software demand is essentially unlimited because most organizations still run on spreadsheets and terrible legacy systems they can't afford to replace. If both assumptions hold, the economics of software development flip entirely. The cost of actually writing code has already collapsed with LLMs. What remains durable are the fuzzy human parts—figuring out what customers actually want, defining what "good" looks like, and making software delightful to use rather than merely functional. This reshaping is already visible in the labor market. Junior developers, whose entire job was turning well-specified tickets into mediocre code that seniors would review and improve, are getting crushed. Stanford research shows 22-to-25-year-olds in AI-exposed jobs are now 19% below their peers in less-exposed fields, with the damage coming from reduced hiring rather than layoffs. The pattern is clear: young workers are losing ground in jobs built on "codified knowledge" (stuff in training data), while experienced workers gain in jobs requiring "tacit knowledge" (learned by doing). Entry-level hiring at big tech companies dropped 65% since 2019, and at early-stage startups it's down 75%. Yet engineering as a share of total hiring actually went up from 46% to 55%, meaning companies are hiring fewer people overall but a bigger chunk are engineers—just not the junior kind whose primary skill was typing. The uncomfortable question this raises: if juniors traditionally became seniors through a decade of code review and gradual skill absorption, where do the next generation of experienced developers come from when that pipeline disappears? The author suggests the job itself has to transform. Instead of learning by writing code under supervision, future developers will need to develop judgment about requirements, design, and user experience—the parts agents can't automate. This isn't a prediction that software development dies; it's a prediction that the title "software developer" will mean something radically different in ten years, focused on the human-judgment end of the spectrum rather than the mechanical production of code.